Data_Viz_CMU

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Part I of Final Project

this template includes major elements of Part I of my final project.

High Level Summary

In 2001, a girl growing up in Kabul had a 6% chance of ever sitting in a classroom. Her younger sister, born in 2010, had a 39% chance. But a girl born in Afghanistan today has almost none. This is not just a story about education. It is a story about what a country becomes when it invests in its girls and what it loses when it takes that investment away.

Over two decades, Afghanistan rebuilt itself around one quiet revolution: girls going to school. Enrollment grew from fewer than 50,000 girls in 2001 to 3.2 million by 2021. Female youth literacy climbed from 11% to 44%. By 2021, one in three university students was a woman. And as girls learned, the economy grew Afghanistan’s GDP rose from $2.8 billion in 2001 to a peak of $20.5 billion in 2014. Education and economic growth moved together, hand in hand.

Then, in August 2021, the Taliban returned to power. Within months, girls were banned from secondary school. By 2022, they were banned from universities. The classrooms went silent. Every girl banned from school is a doctor Afghanistan will never have, a teacher it will never train, an economy it will never build. GDP collapsed by 28% in a single year falling to $14.3 billion in 2021. Between 2021 and 2025, literacy gains stalled, enrollment dropped sharply, and the economic freefall continued.

This project tells that story in two clear phases: what Afghanistan gained when girls were allowed to learn, and what it lost when they were not. The goal is to show policymakers, donors, educators, and the general public that girls’ education is not charity it is economic infrastructure. When girls go to school, economies grow. When they are shut out, economies suffer. And the data proves it.

Project Structure & Story Arc

One Sentence Summary

Afghanistan’s two decades of progress in girls’ education and economic growth — collapsed within a single year of the Taliban’s return, proving that educating girls is not charity, it is economic infrastructure.

User Stories

As a policymaker, I want to understand the economic cost of banning girls from school so that I can make the case for education investment in conflict-affected countries. As a donor or NGO, I want to see clear data on what was gained and lost in Afghanistan so that I can direct funding where it matters most. As a general reader, I want to understand how one policy decision banning girls from school can collapse an entire economy.

Phase 1: The Progress (2001–2021)

Afghanistan starts from near zero. Schools are rebuilt after the Taliban’s first regime. Girls begin enrolling in record numbers. The data tells a clear story of growth:

Female school enrollment rises from under 50,000 in 2001 to 3.2 million by 2021 Female youth literacy climbs from 11% to 44% GDP grows from $2.8 billion in 2001 to a peak of $20.5 billion in 2014 Girls make up one third of all university students by 2021

This phase shows that investment in girls’ education and investment in the economy moved in the same direction up.

Phase 2: The Reversal (2021–2025)

August 2021. The U.S. withdraws. The Taliban return. Within months, girls are banned from secondary school. By 2022, they are banned from universities. The data tells an equally clear story but in the opposite direction:

Female school enrollment drops sharply after 2021 Literacy gains stall and begin reversing for younger generations GDP falls from $19.9 billion in 2020 to $14.3 billion in 2021 a 28% drop in one year International aid is suspended, further deepening the economic collapse

This phase shows the direct cost of removing girls from education not just for the girls themselves, but for the entire country.

The Call to Action

The audience will be called to support organizations working on girls’ education access in Afghanistan and similar contexts. The closing message will be clear: every year a girl is kept out of school, a country pays the price.

Initial sketches

Sketch 1 43117

Sketch 2 82633

Sketch 3 96023

Sketch 4 18706

Primary Data Sources

The core datasets for this project come from three publicly accessible sources. The World Bank Open Data portal provides Afghanistan-specific data on female school enrollment (primary and secondary), female literacy rates, and GDP from 2001 to the present. This is the most reliable and internationally comparable source available and will be the backbone of all three main visualizations in this project.

The UNESCO Institute for Statistics (UIS) provides detailed literacy rate data broken down by gender and age group for Afghanistan, including the female youth literacy rate that rose from 11% in 2001 to 44% by 2021. This dataset allows me to show precisely how the post-2001 rebuilding effort improved female literacy and how those gains are now at risk of reversing.

The Data for Afghanistan portal (dataforafghanistan.org) provides national-level data on school enrollment and government education spending as a percentage of GDP from 2002 to 2022, sourced directly from Afghanistan’s National Statistics and Information Authority and UNESCO. This dataset is especially valuable because it captures the full arc of the story the rise from 2002 to 2019 and the sharp decline after 2021.

How I Plan to Use the Data

The World Bank GDP data will be placed alongside the female enrollment data to show the two phases clearly growth during 2001–2021 and collapse after 2021. The UNESCO literacy data will power the bar chart showing progress over time. The Data for Afghanistan enrollment numbers will be used for the main enrollment line chart. All three datasets together will tell the complete before and after story across every visualization in the project.

Method and medium

I plan to build this project using Shorthand as the primary presentation platform, with data visualizations created in Tableau. Shorthand will allow me to tell this story in a scrollable, cinematic format moving the audience through the two phases with images, text, and embedded interactive charts. Tableau will be used for the enrollment line chart, the GDP line chart, and the literacy bar chart, all of which will be embedded directly into the Shorthand story.

For the opening before/after comparison panel, I will use Datawrapper, which produces clean, publication quality stat comparisons. The final deliverable will be a fully interactive, publicly accessible web story.

References

AI acknowledgements

I used AI to help me organize my written documentation. All research, data selection, topic choice, story structure, and design decisions are entirely my own.